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Projects related to quality-diversity algorithms

Research / Pillars & Groups / Communications & Artificial Intelligence / LEAR / BSc/MSc Topics / Projects related to quality-diversity algorithms
16 January. 2021

Quality-diversity (QD) algorithms are automated search methods that enable the generation of a diverse collection of high-quality solutions. QD algorithms have found a wide range of applications, for example, in robotics, games, airfoil design and others: https://quality-diversity.github.io/ 

During this internship we will explore novel applications of QD and/or improving aspects of QD algorithms, e.g., accelerating them or combining them with deep learning. 

Suggested reading: 

Chatzilygeroudis, K., Cully, A., Vassiliades, V., & Mouret, J. B. (2020). Quality-Diversity Optimization: a novel branch of stochastic optimization. arXiv preprint arXiv:2012.04322. 

Required Skills
Good programming skills (C++ or Python). Knowledge of machine learning, optimization, robotics, neural and evolutionary computation will be considered an advantage.